Anandakumar Amutha

Aim: We aimed to develop a calculator to determine the probability of having HNF1A-MODY (hepatocyte nuclear factor 1 alpha-maturity-onset diabetes of the young) or HNF4A (hepatocyte nuclear factor 4 alpha) -MODY (the commonest forms of MODY) in Asian Indians using clinical and biochemical criteria. Methods: We extracted data on individuals with young-onset diabetes aged n = 29 191) from electronic records. Genetically confirmed HNF1A- and HNF4A-MODY ( n = 55) were selected along with 1000 individuals each of type 1 diabetes (T1D) and type 2 diabetes (T2D). These data sets were used to develop a classification model using logistic regression. The model’s performance was evaluated using receiver operating characteristic (ROC) curves in an internal data set and validated in an external data set. Results: Eight predictive models were constructed, beginning with a basic model that included variables, such as age at diagnosis, body mass index (BMI), parental history, and glycated hemoglobin (HbA1c) (models 1 and 5). High-density lipoprotein (HDL) cholesterol was added in models 2 and 6, stimulated C-peptide in models 3 and 7, and all predictors were combined in models 4 and 8. Models 1 to 4, designed to distinguish MODY from T1D, achieved an ROC-area under the curve (AUC) value ranging from 0.884 to 0.957, while models 5 to 8, aimed at differentiating MODY from T2D, achieved an ROC-AUC value ranging from 0.914 to 0.936. All models demonstrated excellent performance in internal validation, with high five-fold cross-validation c -statistics. An online calculator using these models estimates MODY probability that is accessible at https://mdrf-t1d-calculator.shinyapps.io/MODY/ . Conclusion: We developed an ethnicity-specific calculator to help identify individuals with possible HNF1A-MODY or HNF4A-MODY in Asian Indians. This user-friendly, web-based tool would be helpful to select candidates for genetic testing in this population.

Aims: This study aims to describe the profile of Asian Indians with young‐onset type 1 diabetes (T1D) and type 2 diabetes (T2D) who have ‘low cardiovascular disease (CVD) risk’ and ‘high CVD risk’ based on QRESEARCH risk estimator version 3(QRISK3) and Framingham Risk Score (FRS). It also aims to assess the predictive ability of these risk calculators to estimate CVD risk in this population. Methods: Retrospective data of 18,837 individuals with T1D or T2D with an age of onset of between 10 to 30 years were retrieved from Diabetes Electronic Medical Records. QRISK3 algorithm and FRS were used to estimate the 10‐year risk of CVD. After excluding individuals with preexisting CVD ( n = 175), the QRISK3 score was calculated for 5371, and FRS for 7444 individuals with young‐onset T1D and T2D. CVD risk was categorized as high if the QRISK3 and FRS scores ≥10.0% and low, if p < 0.001). The frequency of high‐risk scores increased with age and was higher among men. The receiver operating characteristic–area under the curve (ROC‐AUC) showed that both scores (QRISK3‐0.788; FRS‐0.746; p = 0.241) predicted 10‐year cardiovascular disease risk well. Conclusion: Both QRISK and FRS were good predictors of CVD in this population. Individuals with young‐onset diabetes have a high propensity to develop cardiovascular disease within 10 years, with T2D having a higher risk than T1D. Regular risk monitoring, lifestyle modifications and medical interventions are essential among individuals with young‐onset T2D and T1D.

Aim: We compared biochemical and clinical data of individuals with type 2 diabetes (T2D) who opted for only teleconsultation (ie, no in-person visit at all), hybrid visits (combining home blood tests and in-person consultation), and fully in-person visits (both tests and consultation in person) at a tertiary care diabetes center. Methods: In this observational cohort study, we retrieved demographic, anthropometric, and biochemical data of 8197 individuals with T2D who sought diabetes care between 2021 and 2023 (384 participants with only teleconsultations, 721 with hybrid visits, and 7092 with fully in-person visits) from the electronic medical records of a chain of tertiary diabetes care centers across India. Results: Individuals who opted for teleconsultation had a shorter duration of diabetes compared with those who opted for hybrid or fully in-person visits. Although participants who opted for a teleconsultation had better glycemic and lipid control at baseline, those who underwent hybrid and in-person visits showed greater improvements in fasting plasma glucose, glycated hemoglobin (A1c), and LDL cholesterol (LDL-C) during follow-up. Improvements in overall ABC target achievement ( A 1c, B lood pressure, and L DL-C) were greater in participants who had in-person visits compared with the other two groups. Conclusion: While teleconsultation is a useful complement to in-person visits, the latter results in better glycemic and lipid control, perhaps due to more effective engagement with the diabetes care team.

Celiac disease (CeD) is an autoimmune condition that is triggered when gluten, the protein component found in wheat, barley, and rye, is consumed. It is not only a disease of the intestines: it is a complex condition resulting from a combination of several hereditary variables working in conjunction with non-genetic reasons. Type 1 Diabetes (T1D) is an autoimmune illness associated with absolute insulin deficiency and severe hyperglycemia in those with genetic vulnerability. T1D is often associated with CeD due to its shared genetic predisposition and immune system dysregulation. CeD is often underdiagnosed or misdiagnosed due to a lack of knowledge of the condition among healthcare professionals and the general public. CeD is often mistaken for many other gastrointestinal disorders, which leads to delays in the treatment and management of the disease, thus leading to various other complications. To address this issue, this study was initiated with a comprehensive literature review from databases such as PubMed, Scopus, Google Scholar, PGIMER, ICMR, and International Diabetes Federation Atlas Reports using keywords like “Type 1 Diabetes,” “Celiac Disease,” and “India.” Studies on CeD prevalence in India, genetic linkages to T1D, related variables, and clinical characteristics were included. Non-relevant populations, non-human studies, and old data were excluded. Narrative synthesis provided a comprehensive picture of CeD and T1D in India. This narrative review aims to enhance the understanding of CeD and T1D and guide the development of effective strategies from the public health perspective, to address CeD at an early stage.

Background: Type 1 diabetes (T1D) has a significant impact on the well-being and behavioral pattern of affected adolescents, and can lead to affective disorders including depression and anxiety. An emphasis on cognitive and behavioral patterns is necessary to aid the stress and emotions associated with the diagnosis of T1D and is an essential part of optimum care. Aim: This study aims to assess the perceptions and behavioral patterns of Asian Indian adolescents diagnosed with T1D. Materials and Methods: Twenty-one adolescents with T1D (between the ages of 10 and 19 years) with a duration of diabetes up to 24 months were identified from the electronic medical records of a large chain of diabetes centers in India. Telephonic interviews were conducted to fill out questionnaires regarding dietary habits, insulin treatment, and physical activity of participants. Results: The majority (81%) of the adolescents interviewed were adapted to their condition. Most received support from their peers and teachers at school (57%), but 85% continued to have cravings for foods that were restricted from their diet. Almost half (42.9%) of participants and their parents experienced high levels of stress during the initial stages of diagnosis. Most (80%) of them were engaged in physical activities such as jogging, walking, dancing, yoga, and cycling. Conclusion: This pilot study suggests that by providing psychological support to adolescents with T1D, it is possible to overcome the stress that accompanies the diagnosis and adaptation to lifestyle changes.